329 Computing & Software Development Tools courses in Westhoughton delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

Duration 2 Days 12 CPD hours This course is intended for Attending students should be new to Jira (this is NOT for experienced users), and are required to have a background in basic Enterprise application development Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment guided by our expert Jira practitioner, students will explore: Getting started with JIRA Using JIRA for Business Projects Using JIRA for Agile Projects Issue Management Field Management Screen Management Workflows and Business Process Searching and Filtering Tracking issues is a critical component of any project management strategy. JIRA provides a web based single repository for creating, tracking and reporting on feature requests, bugs reported, or managing workflow. JumpStart to Jira for End Users is a two-day, lab-intensive course for participants new to Jira, that provides them with a hands-on Jira instance to ?learn by doing?. This course provides essential understanding in the practical use of the Jira in an Agile context, with an emphasis on Best Practices and practical job-ready skills. Getting started with JIRA JIRA Overview Core concepts Terminology Infrastructure Users and Groups JIRA roles Using JIRA for Business Projects Overview of Projects Project types Project screens Tasks and task management Project Management Process Management Using JIRA for Agile Projects Overview of Agile with JIRA (very brief) Kanban overview Running a project with Kanban Configuring agile screen resolving an issue Issue Management Overview of Issues Working with issues Issue cloning Time tracking Issues and comments Tasks and subtasks Field Management Overview of Fields Built-in fields Custom fields Searching Configuring JIRA for fields Screen Management Overview of JIRA screens Working with screens Using screen tabs Issue type screens associating an issue type screen a with a project Customizing JIRA screens Workflow and Business Process Overview of Workflow Mapping business processes Managing workflows Authoring a workflow Updating an existing workflow Workflow schemes Applying a workflow to a project Searching and Reporting Overview of Searching Search screens Basic search Advanced search with JQL Working with search results Reports Dashboards Filters Gadgets Charts Summary and Best Practices Looking back at the ?Big Picture? JIRA Administration Overview Where JIRA fits into the Agile perspective JIRA End-User best practices

Duration 1 Days 6 CPD hours This course is intended for Individuals planning to deploy applications and create application environments on Google Cloud. Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services. Describe ways in which customers have used Google Cloud. Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine. Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore. Make basic use of BigQuery, Google's managed data warehouse for analytics. This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies. Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform. Understand the purpose of and use cases for Identity and Access Management. List the methods of interacting with Google Cloud Platform. Lab: Getting Started with Google Cloud Platform. Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Lab: Deploying Applications Using Google Compute Engine. Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable. Learn how to choose between the various storage options on Google Cloud Platform. Lab: Integrating Applications with Google Cloud Storage. Google Container Engine Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Introduction to Hybrid and Multi-Cloud computing (Anthos). Lab: Deploying Applications Using Google Container Engine. Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand the purpose of and use cases for Google Cloud Endpoints. Lab: Deploying Applications Using App Engine and Cloud Datastore. Deployment and Monitoring Understand the purpose of template-based creation and management of resources. Understand the purpose of integrated monitoring, alerting, and debugging. Lab: Getting Started with Stackdriver and Deployment Manager. Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Lab: Getting Started with BigQuery. Summary and Review Summary and Review. What's Next?.

Duration 1 Days 6 CPD hours This course is intended for Software developers, system administrators, and IT professionals who are focused on Microsoft Windows Overview Configuring Microsoft Windows and Microsoft SQL Server in Google Compute Engine. Deploying ASP.NET MVC applications to Google Compute Engine. Deploying .NET Core applications to Google Compute Engine, Google Compute Engine, and Google Container Engine Learn how to create Windows virtual machines on Google Cloud so that you can deploy and run Microsoft Windows applications. In this course, you'll learn how to run SQL Server in Compute Engine, how to deploy instances across Google Cloud zones, and how to get more out of ASP.NET on Compute Engine, Google Container Engine, and App Engine. Introduction to Google Cloud Platform Scope and structure of GCP. Options for Windows deployment on GCP. GCP interfaces. Windows Workloads on Google Compute Engine Google Compute Engine virtual machine options. Integrating Active Directory with Google Compute Engine virtual machines. Options for running SQL Server in Google Compute Engine. Configuring SQL Server for high availability. Developing ASP.NET MVC applications Model-view-controller structure. Using Microsoft Visual Studio?s Web Project template to develop in ASP.NET. Deploying applications to Microsoft Internet Information Server (IIS) in GCE. Configuring Resilient Workloads Deploying instances across GCP zones. Using instance groups to create pools of virtual machines. Load balancing Windows applications. Delivering Next-Generation ASP.NET Core on GCP Understanding .NET Core and EF Core. Options for deploying ASP.NET Core applications on Google Cloud Platform. Deploying ASP.NET Core applications on Google Compute Engine. Deploying ASP.NET Core applications on Google Container Engine. Deploying ASP.NET Core applications on Google App Engine. Additional course details: Nexus Humans Develop and Deploy Windows Applications on Google Cloud Platform training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Develop and Deploy Windows Applications on Google Cloud Platform course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for This course is appropriate for developers and administrators who intend to use HBase. Overview Skills learned on the course include:The use cases and usage occasions for HBase, Hadoop, and RDBMSUsing the HBase shell to directly manipulate HBase tablesDesigning optimal HBase schemas for efficient data storage and recoveryHow to connect to HBase using the Java API, configure the HBase cluster, and administer an HBase clusterBest practices for identifying and resolving performance bottlenecks Cloudera University?s four-day training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second. Introduction to Hadoop & HBase What Is Big Data? Introducing Hadoop Hadoop Components What Is HBase? Why Use HBase? Strengths of HBase HBase in Production Weaknesses of HBase HBase Tables HBase Concepts HBase Table Fundamentals Thinking About Table Design The HBase Shell Creating Tables with the HBase Shell Working with Tables Working with Table Data HBase Architecture Fundamentals HBase Regions HBase Cluster Architecture HBase and HDFS Data Locality HBase Schema Design General Design Considerations Application-Centric Design Designing HBase Row Keys Other HBase Table Features Basic Data Access with the HBase API Options to Access HBase Data Creating and Deleting HBase Tables Retrieving Data with Get Retrieving Data with Scan Inserting and Updating Data Deleting Data More Advanced HBase API Features Filtering Scans Best Practices HBase Coprocessors HBase on the Cluster How HBase Uses HDFS Compactions and Splits HBase Reads & Writes How HBase Writes Data How HBase Reads Data Block Caches for Reading HBase Performance Tuning Column Family Considerations Schema Design Considerations Configuring for Caching Dealing with Time Series and Sequential Data Pre-Splitting Regions HBase Administration and Cluster Management HBase Daemons ZooKeeper Considerations HBase High Availability Using the HBase Balancer Fixing Tables with hbck HBase Security HBase Replication & Backup HBase Replication HBase Backup MapReduce and HBase Clusters Using Hive & Impala with HBase Using Hive and Impala with HBase Appendix A: Accessing Data with Python and Thrift Thrift Usage Working with Tables Getting and Putting Data Scanning Data Deleting Data Counters Filters Appendix B: OpenTSDB

Duration 3 Days 18 CPD hours This course is intended for This Yellow Belt training is intended for managers and employees from companies or government institutions who want to get acquainted with Lean Six Sigma or (soon) will have to deal with Lean Six Sigma in their own organization Overview During this training you will become acquainted with the essence of Lean Six Sigma and the importance of improvement management. It discusses how a Lean Six Sigma improvement project is approached, who plays an important role in an improvement project, what it yields as an employee or manager if this methodology is introduced in the organization and what should be taken into account when implementing. Theory and practice go hand in hand. The training encourages you to think about the value for your customer and which methodology best suits your role and your value in a process. This makes Lean and Six Sigma understandable and applicable. We also show what is involved in the introduction of LeanSix Sigma and there are various discussions about the introduction and the 'do's and don'ts of Lean Six Sigma. Course Outline Lean & Six Sigma Overview Basic Statistics Lean Six Sigma: the DMAIC Roadmap Lean Six Sigma: Tools Additional course details: Nexus Humans Lean Six Sigma Yellow Belt training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Lean Six Sigma Yellow Belt course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for Network Engineers, Network Administrators, Network Security Engineers, and NOC Administrators Overview Successful completion of this five-day, instructor-led course will help enhance your understanding of how to design, implement, and effectively operate a Prisma SDWAN solution. You will get hands-on experience configuring Prisma SD-WAN with a branch and datacenter, configure policies, and use Prisma SD-WAN services. The Prisma SD-WAN Design and Operation (EDU-238) course describes the next generation Prisma SD-WAN solution, the capability and value it provides over legacy WAN and SD-WAN implementations, and how to configure, operate, and troubleshoot the solution.This course is intended for people who must configure, maintain, and use wide area networks, from data centers, to branches, to the cloud. This class is powered by Cloud Harmonics. Course Outline Module 1 - Solution Overview Module 2 - Branch Design Module 3 - Routing Module 4 - Policy Module #1 - Application Path and QoS Policy Module 5 - Policy Module #2 - NAT, ZBFW and Security Module 6 - Event Policy Management Services Module 7 - DNS and DHCP Services Module 8 - Operations and Troubleshooting Module 9 - CloudBlades Module 10 - Integrating Prisma SD-WAN and Prisma Access for SASE Implementation Module 11 - DevOps Module 12 - Next Steps

Duration 2 Days 12 CPD hours This course is intended for Customers and systems operators that want to learn fundamental AOS concepts and navigate Prism on AHV. Junior IT administrators and business leaders who manage Nutanix clusters in the datacenter and want a formal, hands-on, detailed introduction to Nutanix datacenter administration. The Nutanix Hybrid Cloud Fundamentals course introduces you to the products, capabilities, and technologies that serve as the foundation of Nutanix?s Hybrid Cloud solution.Begin by exploring the history of this technology space, including different types of clouds, and how on-prem and public infrastructures came together to create hybrid operating models. Then, delve deeper into essential Nutanix products ? AOS, AHV, and Prism ? while discussing how these products were designed to solve business challenges.And conclude by discussing certain fundamental aspects involved in operating the Nutanix Hybrid Cloud, such as cluster updates, managing virtual machines, reporting and performance metrics, and more Module 1: Introduction Describe course terminology, such as three-tier architecture, hyperconverged architecture, and public, private, and hybrid clouds. Module 2: Understanding AOS Concepts Describe self-healing architecture Describe replication factor Describe Nutanix multicloud solutions Module 3: Understanding Cluster Management Concepts Explain Prism Element features and benefits Explain Prism Central features and benefits Manage the Image Repository Upgrade the hypervisor and AOS on a cluster Describe Life Cycle Manager. Module 4: Understanding Storage Concepts Define a storage pool and storage container Identify components of AOS Distributed Storage Identify space-saving technologies Module 5: Managing VMs Create and manage virtual machines (VMs) Add a VM to a category Describe Acropolis Dynamic Scheduler (ADS) Describe data locality Module 6: Monitoring VMs and Cluster Health Use metrics to identify performance issues Measure VM performance using Nutanix tools: Health dashboard, Analysis dashboard, Alerts dashboard Use the Support Portal and Insights Module 7:Understanding Data Protection Concepts Describe how to enable data protection on a VM Define a retention policy Define Nutanix Mine Identify the different types of replication targets

Duration 3 Days 18 CPD hours This course is intended for This course is designed for administrators who install, manage, and monitor IBM© DataPower Gateway Appliances. The course is also relevant for developers who administer appliances. Overview Configure an appliance for its initial deployment Download and upgrade the firmware on the DataPower appliances Create and manage user accounts, groups, and domains Configure Secure Sockets Layer (SSL) to and from DataPower Appliances Troubleshoot and debug services by using the problem determination tools, logs, and probes that are provided with the DataPower appliance Configure logging of messages to external locations IBM© DataPower Gateway Appliances are network devices that help secure, integrate, and optimize access to web, web services, mobile, and API workloads. Through instructor-led lectures and hands-on lab exercises, you learn how to run various administrative procedures, from initial installation and setup through ongoing maintenance of the appliances in production. You learn about the available management interfaces, such as the command-line interface (CLI), Web Management graphical interface, and XML Management Interface. You also learn how to use these interfaces to run various administrative tasks, such as upgrading firmware, running backup and restore operations, and configuring user accounts and domains. The course includes some information on upgrading firmware and working with DataPower hardware appliances. Course introductionDataPower deployment environmentsInitial setupManaging firmwareExercise: Upgrading image firmwareDataPower administration overviewUsing CLI and the XML Management Interface to configure appliance accessExercise: Using the CLI and the XML Management Interface to manage DataPower appliancesDataPower services overviewUsing the Web Management Blueprint Console to configure appliance accessTroubleshootingExercise: Using the troubleshooting tools to debug errorsDataPower cryptographic tools and SSL setupExercise: Securing connections with SSLLogging and log targetsExercise: Logging to an external systemCourse summary

Duration 2 Days 12 CPD hours This course is intended for The introductory-level course is geared for software developers, project managers, and IT professionals seeking to enhance their understanding and practical skills in version control and collaboration using GitLab. It's also well-suited for those transitioning from another version control system to GitLab, or those responsible for software development lifecycle within their organization. Whether you are an individual looking to boost your proficiency or a team leader aiming to drive productivity and collaboration, this course will provide the necessary expertise to make the most of GitLab's capabilities. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Gain a firm understanding of the fundamentals of Git and GitLab, setting a solid foundation for advanced concepts. Learn to effectively manage and track changes in your code, ensuring a clean and reliable codebase. Discover ways to streamline your daily tasks with aliases, stashing, and other GitLab workflow optimization techniques. Develop skills in creating, merging, and synchronizing branches, enabling seamless collaboration and version control. Equip yourself with the knowledge to use Git as a powerful debugging tool, saving time and effort when troubleshooting issues. Understand the basics of continuous integration and continuous deployment (CI/CD) in GitLab, helping you automate the software delivery process. Immerse yourself in the dynamic world of GitLab, a leading web-based platform for version control and collaboration, through our intensive two-day course, GitLab Quick Start. Version control systems, such as GitLab, are the backbone of modern software development, enabling teams to work cohesively and maintain a structured workflow. By mastering GitLab, you can improve efficiency, encourage collaboration, and ensure accuracy and reliability within your projects, adding significant value to your organization. Throughout the course you?ll explore various aspects of GitLab, starting from the fundamental principles of source code management to advanced concepts like rebasing and continuous integration/design. Key topics covered include Git and GitLab basics, reviewing and editing commit history, mastering GitFlow and GitLab Flow, branching and merging strategies, and understanding remote repositories. You'll also learn how to utilize Git as a debugging tool and explore the power of GitLab's built-in CI/CD capabilities. The core value of this course lies in its practical application. You'll learn how to effectively manage changes in code with GitLab, allowing you to maintain audit trails, create reproducible software, and seamlessly move from another version control system. Then you?ll learn how to enhance your workflow efficiency using aliases for common commands, saving changes for later use, and ignoring build artifacts. You?ll also explore GitLab's CI/CD, which will enable you to automate your software delivery process. These hands-on labs will walk you through creating, merging, and synchronizing remote branches, configuring Git, troubleshooting using Git as a debugging tool, and setting up GitLab Runner for CI/CD. Each lab is designed to simulate real-world projects, offering you a first-hand experience in managing and contributing to a version control system like GitLab. Introduction to Source Code Management The Core Principles of Change Management The Power to Undo Changes Audit Trails and Investigations Reproducible Software Changing code-hosting platform Moving from another version control system Git and GitLab Introduction and Basics Introduction to Git GitFlow GitLab Flow Trees and Commits Configuring Git Adding, Renaming, and Removing Files Reviewing and Editing the Commit History Reviewing the Commit History Revision Shortcuts Fixing Mistakes Improving Your Daily Workflow Simplifying Common Commands with Aliases Ignoring Build Artifacts Saving Changes for Later Use (Stashing) Branching Branching Basics Listing Differences Between Branches Visualizing Branches Deleting Branches Tagging Merging Merging Basics Merge Conflicts Merging Remote Branches Remote Repositories Remote Repositories Synchronizing Objects with Remotes Tracking Branches Centralizing and Controlling Access Introduction to GitLab Git Repositories on GitLab Daily Workflow Reviewing Branching and Merging Branch Review Merging Basics Rebasing Rebasing Basics Rebasing with Local Branches Rebasing with Remote Branches Interactive Rebasing Squashing Commits Getting Out of Trouble Git as a Debugging Tool Using the Blame Command to See File History Performing a Binary Search Continuous Integration / Continuous Design (CI/CD) How to install GitLab Runner Adding to our example project Breaking down .gitlab-ci.yml Adding .gitlab-ci.yml to our example project Deconstructing an advanced .gitlab-ci.yml file GitLab CI/CD web UI Optional: Resetting Trees Introduction to Resetting Resetting Branch Pointers Resetting Branches and the Index Resetting the Working Directory Making Good Use of the Reset Command Optional More on Improving Your Daily Workflow Interactively Staging Changes Optional: Including External Repositories Submodules Subtrees Choosing Between Submodules and Subtrees Workflow Management Branch Management